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Fil Menczer

Fil Menczer

I am on sabbatical at Yahoo! Labs (Sunnyvale, California) during the 2014-2015 academic year.

I am a Professor of Informatics and Computer Science and the Director of the Center for Complex Networks and Systems Research at the Indiana University School of Informatics and Computing. I also have courtesy appointments in Cognitive Science and Physics, and am affiliated with the Center for Data and Search Informatics and the Biocomplexity Institute. Finally I am a Senior Research Fellow of The Kinsey Institute and a Fellow at the ISI Foundation in Torino, Italy.

Research in my group, NaN, focuses on Web science, social media, social networks, social computing, Web search and data mining, distributed and intelligent Web applications, and modeling of complex information networks.

My calendar is a bit crowded. You may schedule an appointment with Tara Holbrook, our center’s administrative assistant. Or you can try your luck by email, phone (+1-812-856-1377), fax (+1-812-855-0600), or in person (Informatics East room 314).

Prospective students interested in joining my group, NaN, should look at this advice before contacting me. Then, if still interested, they should apply to one of our PhD programs: Informatics (Complex Systems track), Computer ScienceCognitive Science, or a combination. I am usually unable to respond to inquiries from prospective students unless they have already been admitted to one of these programs.

Latest News from the Blog



The Truth about Truthy

MegynKelly.jpg

The Truthy project was misrepresented in “The Kelly File” and “Fox and Friends” broadcasts by Fox News on 26 and 28 Aug 2014. Photo by MattGagnon [public domain] via Wikimedia Commons

For the past four years, researchers at the Center for Complex Networks and Systems Research at the Indiana University School of Informatics and Computing have been studying the ways in which information spreads on social media networks such as Twitter. This basic research project is federally funded, like a large percentage of university research across the country.

The project, dubbed “Truthy,” makes use of complex computer models to analyze the sharing of information on social media to determine how popular sentiment, user influence, attention, social network structure, and other factors affect the manner in which information is disseminated. Additionally, an important goal of the Truthy project is to better understand how social media can be abused.

In recent weeks, the Truthy project has come under criticism from some, who have misrepresented its goals. Contrary to these claims, the Truthy project is not designed and has not been used to create a database of political misinformation to be used by the federal government to monitor the activities of those who oppose its policies.

Truthy is not intended and is not capable to determine whether a statement constitutes “misinformation.” The target is the study of the structural patterns of information diffusion.

For example, an email sent simultaneously to a million addresses is likely spam, even if we have no automatic way to determine whether its content is true or false. The assumption behind the Truthy effort is that an understanding of the spreading patterns may facilitate the identification of abuse, independent from the nature or political color of the communication.

The Truthy platform is not informed by political partisanship. While it provides support to study the evolution of communication in all portions of the political spectrum, the machine learning algorithms used to identify suspicious patterns of information diffusion are entirely oblivious to the possibly political partisanship of the messages.

8/28/2014 Update: Despite the clarifications in this post, Fox News and others continued to perpetrate their attacks to our research project and to the PI personally. Their accusations are based on  false claims, supported by bits of text and figures selectively extracted from our writings and presented completely out of context, in misleading ways. None of the researchers were contacted for comments before these outlandish conspiracy theories were aired and published. There is a good dose of irony in a research project that studies the diffusion of misinformation becoming the target of such a powerful disinformation machine.

9/3/2014 Update: David Uberti wrote an accurate account of recent events in Columbia Journalism Review.

10/18/2014 Update: Unfortunately, the smear campaign against our research project continues, with misleading information echoed in an op-ed by FCC Commissioner Ajit Pai. Not that he bothered to contact any of the researchers with questions about the accuracy of his allegations.

10/22/2014 Update: Amid news reports that the chairman of the House Science, Space and Technology Committee initiated an investigation into the NSF grant supporting our project, read our interview in the Washington Post’s Monkey Cage setting the record straight about our research.

Read below for a primer on Truthy. More detailed information can be found on the Truthy website and publications.

Facts about Truthy:

  • Truthy is a research project of the Center for Complex Networks and Systems Research at the IU School of Informatics and Computing. It aims to study how information spreads on social media, such as Twitter.
  • The project has focused on domains such as news, politics, social movements, scientific results, and trending social media topics. Researchers develop theoretical computer models and validate them by analyzing public data, mainly from the Twitter streaming API.
  • Social media posts available through public APIs are processed without human intervention or judgment to visualize and study the spread of memes. We aim to build a platform to make these analytic tools easily accessible to social scientists, reporters, and the general public.
  • An important goal of the project is to help mitigate misuse and abuse of social media by helping us better understand how social media can be potentially abused. For example: when social bots are used to create the appearance of human-generated communication (hence the name “truthy”).  We study whether it is possible to automatically differentiate between organic content and so-called “astroturf.”
  • Examples of research to date include analyses of geographic and temporal patterns in movements like Occupy Wall Street, societal unrest in Turkey, the polarization of online political discourse, the use of social media data to predict election outcomes and stock market movements, and the geographic diffusion of trending topics.
  • On the more theoretical side, we have studied how individuals’  limited attention span affects what information we propagate and what social connections we make, and how the structure of social networks can help predict which memes are likely to become viral.
  • Hundreds of researchers across the U.S. and the world are studying similar issues based on the same data and with analogous goals — these topics were studied well before the advent of social media.
  • The results of our research have been covered widely in the press, published in top peer-reviewed journals, and presented at top conferences worldwide. All papers are publicly available.

Finally, the Truthy research project is not:

  • a political watchdog
  • a government probe of social media
  • an attempt to suppress free speech
  • a way to define “misinformation”
  • a partisan political effort
  • a database tracking hate speech


Best paper award at WebSci14

world_turkeyCongratulations to Onur Varol, Emilio Ferrara, Chris Ogan, Fil Menczer, and Sandro Flammini for winning the ACM Web Science 2014 Best Paper Award with their paper Evolution of online user behavior during a social upheaval (preprint). In the paper, the authors study the pivotal role played by Twitter during the political mobilization of the Gezi Park movement in Turkey. By analyzing over 2.3 million tweets produced during 25 days of protest in 2013, the authors show that similarity in trends of discussion mirrors geographic cues. The analysis also reveals that the conversation becomes more democratic as events unfold, with a redistribution of influence over time in the user population. Finally, the study highlights how real-world events, such as political speeches and police actions, affect social media conversations and trigger changes in individual behavior.

Congratulations also go to Luca Aiello and Rossano Schifanella, both former visitors and members of CNetS, who won the Best Presentation Award with their talk on Reading the Source Code of Social Ties (preprint).



WebSci14

websci14We are excited to announce that the ACM Web Science 2014 Conference will be hosted by our center on the beautiful IUB campus  June 23–26, 2014. Web Science studies the vast information network of people, communities, organizations, applications, and policies that shape and are shaped by the Web, the largest artifact constructed by humans in history. Computing, physical, and social sciences come together, complementing each other in understanding how the Web affects our interactions and behaviors. Previous editions of the conference were held in Athens, Raleigh, Koblenz, Evanston, and Paris. The conference is organized on behalf of the Web Science Trust by general co-chairs Fil Menczer, Jim Hendler, and Bill Dutton. Follow us on Twitter and see you in Bloomington!



DESPIC team presents Bot Or Not demo and six posters at DoD meeting

IU Bot or Bot poster The DESPIC team at the Center for Complex Systems and Networks Research (CNetS) presented a demo of a new tool named BotOrNot at a DoD meeting held in Arlington, Virginia on April 23-25, 2014.  BotOrNot (truthy.indiana.edu/botornot) is a tool to automatically detect whether a given Twitter user is a social bot or a human. Trained on Twitter bots collected by our lab and the infolab at Texas A&M University, BotOrNot analyzes over a thousand features from the user’s friendship network, content, and temporal information in real time and estimates the degree to which the account may be a bot. In addition to the demo, the DESPIC team (including colleagues at the University of Michigan)  presented several posters on Scalable Architecture for Social Media ObservatoryMeme Clustering in  Streaming DataPersuasion Detection in Social StreamsHigh-Resolution Anomaly Detection in Social Streams, and Early Detection and Analysis of Rumors. See more coverage of BotOrNot on PCWorld, IDS, BBCPolitico, and MIT Technology Review.



Congratulations to Dr. Lilian Weng!

Lilian Weng with her PhD committee

Lilian Weng with her PhD committee

Congratulations to Lilian Weng, who successfully defended her Informatics PhD dissertation titled Information diffusion on online social networks. The thesis provides insights into information diffusion on online social networks from three aspects: people who share information, features of transmissible content, and the mutual effects between network structure and diffusion process. The first part delves into the limited human attention. The second part of Dr. Weng’s dissertation investigates properties of transmissible content, particularly into the topic space. Finally, the thesis presents studies of how network structure, particularly community structure, influences the propagation of Internet memes and how the information flow in turn affects social link formation. Dr. Weng’s work can contribute to a better and more comprehensive understanding of information diffusion among online social-technical systems and yield applications to viral marketing, advertisement, and social media analytics. Congratulations from her colleagues and committee members: Alessandro Flammini, YY Ahn, Steve Myers, and Fil Menczer!



New York Times and The Good Wife on Socialbots

image by Niv Bavarsky

The Good Wife

A scene from an episode of The Good Wife inspired by our work on socialbots

On August 11, 2013, the New York Times published an article by Ian Urbina with the headline: I Flirt and Tweet. Follow Me at #Socialbot. The article reports on how socialbots (software simulating people on social media) are being designed to sway elections, to influence the stock market, even to flirt with people and one another. Fil Menczer is quoted: “Bots are getting smarter and easier to create, and people are more susceptible to being fooled by them because we’re more inundated with information.”  The article also mentions the Truthy project and some of our 2010 findings on political astroturf.

Inspired by this, the writers of The Good Wife consulted with us on an episode in which the main character finds that a social news site is using a socialbot to bring traffic to the site, defaming her client. The episode aired on November 24, 2013, on CBS (Season 5 Episode 9, “Whack-a-Mole”). Good show!